Variable depth streamer srme

ABSTRACT

Methods and systems for variable wavelet correction are described. A variable depth dataset is deghosted before presentation to a multiples prediction step of multiples elimination model. In another aspect, the multiples prediction is reghosted before presentation to and adaptive subtraction step of the multiples elimination model. A source-side zero-phasing signature can be applied before deghosting and a predefined gain can be applied in the low and high frequency sides as part of deghosting and reghosting to compensate for the squaring effect produced by convolving wavelets.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/600,270, filed on Aug. 31, 2012, entitled “Variable Depth StreamerSRME”, which is related to and claims priority from U.S. ProvisionalPatent Application No. 61/585,431, filed Jan. 11, 2012, entitled“BroadSeis SRME,” to Ronan Sablon, the disclosure of which isincorporated herein by reference.

TECHNICAL FIELD

Embodiments of the subject matter disclosed herein generally relate tomethods and systems for seismic data processing and, more particularly,to mechanisms and techniques for eliminating 2D/3D surface relatedmultiples associated with variable-depth streamer data processing.

BACKGROUND

Marine-based seismic data acquisition and processing techniques are usedto generate a profile (image) of a geophysical structure (subsurface) ofthe strata underlying the seafloor. This profile does not necessarilyprovide an accurate location for oil and gas reservoirs, but it maysuggest, to those trained in the field, the presence or absence of oiland/or gas reservoirs. Thus, providing an improved image of thesubsurface in a shorter period of time is an ongoing process.

The acquisition of data in marine-based seismic methods usually producesdifferent results in source strength and signature based on differencesin near-surface conditions. Further data processing and interpretationof seismic data requires correction of these differences in the earlystages of processing. Surface-Related Multiples Elimination (SRME) is atechnique commonly used to predict a multiples model from conventionalflat streamer data. Attenuating the surface-related multiples is basedon predicting a multiples model, adapting the multiples model andsubtracting the adapted multiples model from the input streamer data.

Obtaining accuracy with the conventional method requires a generaltwo-step, pre-conditioning process. First, the input data is adjusted toa sea-level datum and second, a designature is applied to the input datasuch that the input traces are zero-phase. One of the key challenges ofthe conventional method is adjusting the standard SRME technique for usewith variable depth streamer data, i.e., seismic data from streamersthat are at a greater depth as you move from a near offset to a greateroffset.

Compared to conventional same depth streamer data, processing variabledepth streamer data requires a significant processing change withrespect to receiver ghosts. In conventional same depth streamer dataprocessing, both source and receiver ghosts are included in a waveletand are assumed to be consistent from streamer offset to streameroffset. On the contrary, in a variable depth streamer dataset, thereceiver ghosts change from near streamer offsets to far streameroffsets, breaking an implicit assumption of constant depth streamersassociated with many processing steps including SRME and thereforecannot be included in the wavelets.

Attempts to correct the conventional method for variable depth streamershave been made based on a pre-stack or post-stack joint deconvolutionfor removing the receiver ghosts from the final image. A zero-phasingdesignature is applied for the source side only, which means the inputwavelet for the SRME processing retains the zero-phased receiver ghosts.The conventional SRME technique was not defined to handle these types ofwavelet variations, i.e., by convolving traces with different receiverghosts, and therefore the conventional SRME produces a multiples modelwith mismatched wavelets.

The mismatched wavelet problem can be partially solved in the adaptivesubtraction part of the process, through wavelet adjustment in thecommon channel domain, but the effectiveness of this approach does notmeet the quality of a similar analysis with constant depth streamerdata. Further, this attempt leaves many high-frequencies residualmultiples and the low-frequencies multiples cannot be properlyaddressed.

Accordingly, it would be desirable to provide systems and methods thatavoid the afore-described problems and drawbacks, and improve themultiples model prediction for variable-depth streamer data and theaccuracy of the final image.

SUMMARY

According to an exemplary embodiment, a method, stored in a memory andexecuting on a processor, for correcting wavelet variations associatedwith a variable depth streamer configuration for seismic datacollection, the method comprises processing a recorded variable-depthdatum pre-stack dataset, in a shot gather domain, by deghosting thepre-stack dataset wherein all multiples orders are processed; andoutputting a deghosted pre-stack dataset wherein the deghosted pre-stackdataset is normalized to a sea-surface datum and provided to a multipleselimination technique.

According to another exemplary embodiment, a system for correctingwavelet variations associated with a variable-depth streamerconfiguration, the system comprises a dataset containing a plurality ofstreamer variable-depth input trace data; one or more processorsconfigured to execute computer instructions and a memory configured tostore said computer instructions wherein said computer instructionsfurther comprises a deghosting component for processing a recordedvariable-depth datum pre-stack dataset, in a shot gather domain, whereinall multiples orders are processed; and an output component foroutputting a deghosted pre-stack dataset wherein said deghostedpre-stack dataset is normalized to a sea-surface datum and provided to amultiples elimination technique.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of the specification, illustrate one or more embodiments and,together with the description, explain these embodiments. In thedrawings:

FIG. 1 is a schematic diagram illustrating a marine-based seismic dataacquisition system with a variable depth streamer and up-going rays;

FIG. 2 is a schematic diagram illustrating a marine-based seismic dataacquisition system with a variable depth streamer and down-going rays;

FIG. 3 is a flowchart illustrating a method for variable waveletcorrection;

FIG. 4 is a schematic diagram illustrating a system for variable waveletcorrection comprising a deghosting component and an output component;

FIG. 5 is a schematic diagram illustrating a system for variable waveletcorrection comprising a deghosting component, an output component and areghosting component;

FIG. 6 is a schematic diagram of a computerized system that implementsvarious methods according to an exemplary embodiment;

FIG. 7 is a composite schematic diagram of an input wavelet based on avariable depth streamer in 7 a, a standard SRME wavelet prediction in 7b and an exemplary embodiment with a variable wavelet correction appliedto the input data as part of a standard SRME wavelet prediction in 7 c;and

FIG. 8 is a composite schematic diagram with 8 a depicting an inputspectrum from a variable depth streamer versus a spectrum predicted by astandard SRME technique based on variable depth streamer data and 8 bdepicting an input spectrum from a variable depth streamer versus aspectrum predicted by an exemplary embodiment variable waveletcorrection applied to the variable depth streamer data before a standardSRME technique prediction.

DETAILED DESCRIPTION

The following description of the exemplary embodiments refers to theaccompanying drawings. The same reference numbers in different drawingsidentify the same or similar elements. The following detaileddescription does not limit the invention. Instead, the scope of theinvention is defined by the appended claims. Some of the followingembodiments are discussed, for simplicity, with regard to theterminology and structure of estimating more reliable surface-consistentattributes using a common inversion scheme. However, the embodiments tobe discussed next are not limited to these configurations, but may beextended to other arrangements as discussed later.

Reference throughout the specification to “one embodiment” or “anembodiment” means that a particular feature, structure or characteristicdescribed in connection with an embodiment is included in at least oneembodiment of the subject matter disclosed. Thus, the appearance of thephrases “in one embodiment” or “in an embodiment” in various placesthroughout the specification is not necessarily referring to the sameembodiment. Further, the particular features, structures orcharacteristics may be combined in any suitable manner in one or moreembodiments.

In order to provide a context for the subsequent exemplary embodiments,a description of aspects and terminology is hereby included. The methodsand systems described herein generate and receive P-waves. A P-wave isthe wave studied in conventional seismic data and is an elastic bodywave or sound wave in which particles oscillate in the direction thewave propagates. A streamer is a line towed by a streamer vessel andcontaining a plurality of receivers for collecting seismic data from thereflected wave. A variable-depth streamer indicates that the depth ofthe receivers from the surface of the sea varies as you travel along thelength of the streamer.

In a further description of terminology, a shotpoint is one of a numberof locations or stations at a surface datum at which a seismic source isactivated. A seismic trace is the seismic data recorded, by one channel,after the seismic source has been fired. The seismic trace representsthe response of the elastic wave field to velocity and density contrastsacross interfaces of layers of rock or sediments in the seabed as energytravels from the seismic source through the subsurface to a receiver orreceiver array. Further, a seismic inversion is a process oftransforming seismic reflection data into a quantitative propertydescription of a strata description of an underground location andpossibly a reservoir containing natural resources such as oil or gas.

Looking now to FIG. 1, a context diagram illustrates the previouslydescribed aspects for an up-going ray path 100. A shot is fired at ashotpoint 102 near the sea surface 104 to propagate a series of waves106, 108, 110 reflected off the sea floor and collected by the receivers114 attached to the streamer 112. The waves are reflected by the seasurface 104 at different times after the shot is fired and at differentangles. The reflected waves are detected by receivers 114 attached tothe streamers 112 wherein a direct wave 106 can be recorded inconjunction with reflected waves 108, 110. A recording device, aboardthe tow vessel 116, collects the seismic data from the receivers andrecords the data for future analysis. It should be noted in theexemplary embodiment that computations on the recorded data can occur inthe recording device or can occur in another location after the seismicdata has been transferred. Looking to FIG. 2, a similar diagramillustrates the fact that waves 202, 204, 206 can also be recorded in adown-going ray path 200 and the same receiver 208 can receive waves 202,204, 206 that have been reflected a variable and different number oftimes before reaching a receiver 208.

Looking now to FIG. 3, an exemplary method embodiment of a variablewavelet correction 300 is depicted. Starting at step 302 of theexemplary method embodiment, the variable wavelet correction 300 methodprocesses a recorded pre-stack dataset. In another aspect of theexemplary method embodiment step 302, the recorded pre-stack dataset iscomprises a variable depth datum based on the characteristics of thevariable depth streamer and the corresponding variable depths of thereceivers attached to the streamer. Further, in step 302 of theexemplary method embodiment, the processing occurs in a shot gatherdomain and all multiples orders are processed.

Next, at step 304 of the exemplary method embodiment, the variablewavelet correction 300 outputs a deghosted pre-stack dataset for furtherprocessing. Further, in step 304 of the exemplary method embodiment, thedeghosted pre-stack dataset is normalized to a sea-level datum. Itshould be noted in the exemplary method embodiment that the normalizedpre-stack dataset is now suitable for processing by multiple eliminationtechniques unaware of a variable depth datum. It should be noted in theexemplary embodiment that the deghosting and reghosting of the describedexemplary embodiments can be accomplished by a method such as thatdescribed in U.S. patent application Ser. No. 13/334,776 entitled“Device and Method for Deghosting Variable Depth Streamer Data” byGordon Poole, the disclosure of which is incorporated herein byreference.

Looking now to FIG. 4, an exemplary embodiment of a system for variablewavelet correction 400 is depicted. The variable wavelet correctionsystem 400 comprises a deghosting component 402 and an output component404. It should be noted in the exemplary embodiment that the outputcomponent provides a deghosted pre-stack dataset to a multiplesprediction component of a multiples elimination technique.

Continuing with the exemplary embodiment, the deghosting component 402performs a two-dimensional pre-stack deghosting in the shot gatherdomain. It should be noted in the exemplary embodiment that thedeghosting component 402 can also operate on three-dimensional pre-stackdatasets. In another aspect of the exemplary embodiment, the deghostingcomponent 402 applies a source-side zero-phasing designature before thedeghosting of the pre-stack dataset. It should be noted in the exemplaryembodiment that a result of the deghosting by the deghosting component402 is that the pre-stack data has been shifted form the recordedvariable depth datum to a sea surface datum. In another aspect of theexemplary embodiment, the deghosting component 402 applies a pre-definedgain in the low and high frequency sides of the deghosting forcompensating for the squaring effect associated with convolving twowavelets.

Next in the exemplary embodiment, the output component 404 formats thedeghosted pre-stack dataset to a format acceptable for the multiplesprediction component of the selected multiples elimination technique. Inanother aspect of the exemplary embodiment the output component deliversthe ghost free formatted pre-stack dataset to the model predictioncomponent of the selected multiples elimination technique and the modelprediction component generates a ghost free multiples model based on theghost free data.

Looking now to FIG. 5, another exemplary embodiment of a system forvariable wavelet correction 500 is depicted. The variable waveletcorrection 500 system comprises a deghosting component 402 and an outputcomponent 404 as described previously, and a reghosting component 502.Continuing with the exemplary embodiment, the reghosting component 502processes the multiples model produced by the multiples predictioncomponent of the selected multiples elimination technique and reghoststhe predicted multiples model in the shot-gather domain. In anotheraspect of the exemplary embodiment, the pre-stack reghosting inserts themultiples model from the sea-surface datum pre-stack dataset in therecorded datum pre-stack dataset. In another aspect of the exemplaryembodiment, the deghosting component 402 applies a pre-defined gain inthe low and high frequency sides of the deghosting for compensating forthe squaring effect associated with convolving two wavelets. Further inthe exemplary embodiment, the deghosting component delivers thereghosted pre-stack dataset to the output component 404.

Continuing with the exemplary embodiment, it should be noted that theoutput component 404 further comprises the capability to format thereghosted pre-stack dataset to a format acceptable to the adaptivesubtraction component of the selected multiples elimination technique.It should be noted in the exemplary embodiment that the reghostedpre-stack dataset allows the adaptive subtraction component of theselected multiples elimination technique to efficiently address theentire frequency range of the pre-stack dataset. It should be noted inthe exemplary embodiment that the selected multiples eliminationtechnique includes but is not limited to Surface Related MultiplesElimination (SRME) technique, Shallow Water Demultiple technique,Convolution Inter-bed Multiples technique, Radon Demultiple techniqueand Tau-P Deconvolution technique or any demultiple technique whichcreates a multiples model for subtraction from the input data.

The computing device or other network nodes involved in the variablewavelet correction in connection with the above described embodimentsmay be any type of computing device capable of processing andcommunicating pre-stack datasets. An example of a representativecomputing system capable of carrying out operations in accordance withthe servers of the exemplary embodiments is illustrated in FIG. 6.Hardware, firmware, software or a combination thereof may be used toperform the various steps and operations described herein. The computingstructure 600 of FIG. 6 is an exemplary computing structure that may beused in connection with such a system.

The exemplary computing arrangement 600 suitable for performing theactivities described in the exemplary embodiments may include apre-stack dataset processing server. Such a server 601 may include acentral processor (CPU) 602 coupled to a random access memory (RAM) 604and to a read-only memory (ROM) 606. The ROM 606 may also be other typesof storage media to store programs, such as programmable ROM (PROM),erasable PROM (EPROM), etc. The processor 602 may communicate with otherinternal and external components through input/output (I/O) circuitry608 and bussing 610, to provide control signals and the like. Theprocessor 602 carries out a variety of functions as is known in the art,as dictated by software and/or firmware instructions.

The server 601 may also include one or more data storage devices,including hard and floppy disk drives 612, CD-ROM drives 614, and otherhardware capable of reading and/or storing information such as DVD, etc.In one embodiment, software for carrying out the above discussed stepsmay be stored and distributed on a CD-ROM 616, diskette 618 or otherform of media capable of portably storing information. These storagemedia may be inserted into, and read by, devices such as the CD-ROMdrive 614, the disk drive 612, etc. The server 601 may be coupled to adisplay 620, which may be any type of known display or presentationscreen, such as LCD displays, plasma display, cathode ray tubes (CRT),etc. A user input interface 622 is provided, including one or more userinterface mechanisms such as a mouse, keyboard, microphone, touch pad,touch screen, voice-recognition system, etc.

The server 601 may be coupled to other computing devices, such as thelandline and/or wireless terminals and associated watcher applications,via a network. The server may be part of a larger network configurationas in a global area network (GAN) such as the Internet 628, which allowsultimate connection to the various landline and/or mobile client/watcherdevices.

The disclosed exemplary embodiments provide a user terminal, a system, amethod and a computer program product for variable wavelet correctionassociated with seismic data. It should be understood that thisdescription is not intended to limit the invention. On the contrary, theexemplary embodiments are intended to cover alternatives, modificationsand equivalents, which are included in the spirit and scope of theinvention. Further, in the detailed description of the exemplaryembodiments, numerous specific details are set forth in order to providea comprehensive understanding of the invention. However, one skilled inthe art would understand that various embodiments may be practicedwithout such specific details.

Although the features and elements of the present exemplary embodimentsare described in the embodiments in particular combinations, eachfeature or element can be used alone without the other features andelements of the embodiments or in various combinations with or withoutother features and elements disclosed herein. The methods or flow chartsprovided in the present application may be implemented in a computerprogram, software, or firmware tangibly embodied in a computer-readablestorage medium for execution by a general purpose computer or aprocessor.

The results of an exemplary embodiment of the aforementioned variablewavelet correction are illustrated in a comparison between FIGS. 7 a, 7b and 7 c and FIGS. 8 a and 8 b. In the example depicted in FIG. 7, FIG.7 a depicts an input wavelet with a variable-depth streamer, FIG. 7 bdepicts the input wavelet after a standard SRME technique is applied andFIG. 7 c depicts the input wavelet after an exemplary embodimentvariable wavelet correction is applied in conjunction with a standardSRME technique. It is clear that when the standard SRME technique isapplied to a variable-depth datum as shown in FIG. 7 b, incorrectwavelets are predicted leading to unacceptable errors in the technique.In comparison, FIG. 7 c shows an exemplary embodiment variable waveletcorrection of the variable-depth streamer data leading to a predictionmatching the input wavelet data of FIG. 7 a.

In another example of the results of an exemplary embodiment, depictedin FIG. 8, FIG. 8 a depicts an input data spectrum 802 with a standardSRME spectrum 804 for variable depth streamer data while FIG. 8 bdepicts the same variable depth input data spectrum 802 in comparison toan exemplary embodiment variable wavelet correction 806 in conjunctionwith a standard SRME technique. As is easily seen in FIG. 8 a, thepredicted spectrum 804 based on a standard SRME technique does notproperly map to the input spectrum. Looking to exemplary embodiment FIG.8 b, it is clear that the exemplary embodiment variable waveletcorrection added to a standard SRME technique enhances the accuracy ofthe technique. It should be noted that the variable wavelet correctionprovides similar results with other demultiples techniques.

The above-disclosed exemplary embodiments provide a system and a methodfor variable wavelet correction. It should be understood that thisdescription is not intended to limit the invention. On the contrary, theexemplary embodiments are intended to cover alternatives, modificationsand equivalents, which are included in the spirit and scope of theinvention as defined by the appended claims. Further, in the detaileddescription of the exemplary embodiments, numerous specific details areset forth in order to provide a comprehensive understanding of theclaimed invention. However, one skilled in the art would understand thatvarious embodiments may be practiced without such specific details.

Although the features and elements of the present exemplary embodimentsare described in the embodiments in particular combinations, eachfeature or element can be used alone without the other features andelements of the embodiments or in various combinations with or withoutother features and elements disclosed herein. Further, it is noted thatthe above embodiments may be implemented in software, hardware or acombination thereof. It is also noted that although the previouslydescribed exemplary embodiments refer to land-based seismic dataacquisition, the methods and systems described herein are equallyapplicable to marine based seismic data acquisition.

This written description uses examples of the subject matter disclosedto enable any person skilled in the art to practice the same, includingmaking and using any devices or systems and performing any incorporatedmethods. The patentable scope of the subject matter is defined by theclaims, and may include other examples that occur to those skilled inthe art. Such other examples are intended to be within the scope of theclaims.

What is claimed is:
 1. A method, stored in a memory and executing on aprocessor, for correcting wavelet variations associated with a variabledepth streamer configuration for seismic data collection, said methodcomprising: processing a recorded variable-depth datum pre-stackdataset, in a shot gather domain, by deghosting said pre-stack datasetwherein all multiples orders are processed; and outputting a deghostedpre-stack dataset wherein said deghosted pre-stack dataset is normalizedto a sea-surface datum and provided to a multiples eliminationtechnique.
 2. The method of claim 1, further comprising a pre-stackreghosting of a multiples model from said multiples eliminationtechnique, in said shot gather domain, wherein said multiples modelgenerated from said sea-surface datum is applied to said recorded datumto output a reghosted variable depth pre-stack dataset.
 3. The method ofclaim 2, wherein a predefined gain is applied to low frequency and highfrequency sides during said pre-stack reghosting.
 4. The method of claim1, wherein a predefined gain is applied to low frequency and highfrequency sides during said pre-stack deghosting.
 5. The method of claim1, wherein a source-side zero-phasing designature is applied to saidrecorded datum pre-stack dataset prior to said deghosting.
 6. The methodof claim 5, wherein said deghosted pre-stack dataset is input to amultiples prediction of a Surface Related Multiples Elimination (SRME)technique.
 7. The method of claim 5, wherein said deghosted pre-stackdataset is input to a multiples prediction of a Shallow Water Demultipletechnique.
 8. The method of claim 5, wherein said deghosted pre-stackdataset is input to a multiples prediction of a Convolution Inter-bedmultiples technique.
 9. The method of claim 5, wherein said deghostedpre-stack dataset is input to a multiples prediction of a RadonDemultiple technique.
 10. The method of claim 5, wherein said deghostedpre-stack dataset is input to a multiples prediction of a Tau-PDeconvolution technique.
 11. The method of claim 1, wherein saidrecorded datum pre-stack dataset and said deghosted pre-stack dataset istwo-dimensional data.
 12. The method of claim 1, wherein said recordeddatum pre-stack dataset and said deghosted pre-stack dataset isthree-dimensional data.
 13. The method of claim 2, wherein saidreghosted pre-stack dataset is input to an adaptive subtraction processof a demultiples model.
 14. A system for correcting wavelet variationsassociated with a variable-depth streamer configuration, said systemcomprising: a dataset containing a plurality of streamer variable-depthinput trace data; one or more processors configured to execute computerinstructions and a memory configured to store said computer instructionswherein said computer instructions further comprise: a deghostingcomponent for processing a recorded variable-depth datum pre-stackdataset, in a shot gather domain, wherein all multiples orders areprocessed; and an output component for outputting a deghosted pre-stackdataset wherein said deghosted pre-stack dataset is normalized to asea-surface datum and provided to a multiples elimination technique. 15.The system of claim 14, further comprising a reghosting component forreghosting a multiples model, in said shot gather domain, wherein saidmultiples model is generated from said sea-surface datum and is appliedto said recorded variable-depth datum for outputting a reghostedvariable-depth pre-stack dataset.
 16. The system of claim 14, whereinsaid deghosting component further comprises applying a predefined gainto low frequency and high frequency sides.
 17. The system of claim 15,wherein said reghosting component further comprises applying apredefined gain to low frequency and high frequency sides.
 18. Thesystem of claim 16, wherein said deghosting component further comprisesapplying a source-side zero-phasing designature to said recordedvariable-depth datum pre-stack dataset before said deghosting.
 19. Thesystem of claim 14, wherein said streamer variable-depth input tracedata is two-dimensional data.
 20. The system of claim 14, wherein saidstreamer variable-depth input trace data is three-dimensional data.